Physical network infrastructures used by a broadband data service providers generally includes edge network segments to which customer devices are attached. In the cable television industry, the edge network segments include a Hybrid Fiber Coaxial physical infrastructure over which data is transferred using a DOCSIS set of standards. In the telecommunications industry, the edge network segments include Digital Subscriber Loop (DSL) connections between Broadband Remote Access Servers (BRAS) and the customer device(s). In both of these industries, edge network segments using WiFi access standards are also being deployed.
Digital service providers allocate bandwidth based on an over-subscription model in which the sum of all the allowed maximum data transfer rates for all customers attached to a physical segment greatly exceeds the actual available bandwidth of the segment. Such over-subscription models rely on statistical multiplexing based on assumptions that not all customers actively transfer data at the same time, for example. However, customer demand for more bandwidth per segment is increasing rapidly due in large part to the availability of content over the Internet such as video.
As customer demand for bandwidth rapidly increases, edge network segments are becoming increasingly congested. In some areas, the demand for additional bandwidth on a network edge segment exceeds the bandwidth available on the segment. When this occurs, customers may not have access to their desired amount of bandwidth. This reduction in bandwidth for each customer can cause customer dissatisfaction resulting lost revenue for the digital service providers.
Digital service providers may need to incur substantial costs to add capacity or may use a number of congestion management techniques to mitigate congestion on edge network segments. For example, providers may use active management techniques which reduce the permitted bandwidth for a subset of customers who are using the greatest amount of bandwidth. This technique restricts a relatively small number of customers to benefit the remaining customers.
Currently used active management techniques may not be optimal for congestion management and can be ineffective. For example, one common congestion management technique reduces a maximum allowed transfer rate for customers with high usage of the segment for a period of time. This technique reduces the maximum allowed rate be a fixed amount, which may be based on a provisioned maximum allowed rate for a customer. This technique can be ineffective, for example, when congestion is severe enough that the customers are only achieving less than the reduced maximum allowed rate. In that case the rate change has no effect. Another congestion management technique enforces maximum allowed rates for various types of digital traffic. However, this technique does not directly measure the congestion state of edge network segments and may therefore result in too much or too little rate limiting for optimal congestion management.